Nothing

```
##
##
## All code copyright (c) 2013 UPC/UB
## All accompanying written materials copyright (c) 2013 UPC/UB
##
##
## This program is free software: you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation, either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program. If not, see <http://www.gnu.org/licenses/>.
##
PLSDA <- function (Xtrain, Ytrain, Xtest = NULL, ncomp, nruncv = 0, alpha = 2/3,
priors = NULL) {
ntrain <- nrow(Xtrain)
Ytrain <- as.factor(Ytrain)
if (is.vector(Xtest)) {
Xtest <- matrix(Xtest, 1, length(Xtest))
}
if (is.null(Xtest)) {
Xtest <- Xtrain
}
if (nruncv == 0 & length(ncomp) > 1)
stop("Since length(ncomp)>1, nruncv must be >0")
if (nruncv > 0) {
ncomp <- pls.lda.cv(Xtrain, Ytrain, ncomp = ncomp, nruncv = nruncv,
alpha = alpha, priors = priors)
}
pls.out <- pls.regression(Xtrain = Xtrain, Ytrain = transformy(Ytrain),
Xtest = NULL, ncomp = ncomp)
Ztrain <- as.data.frame(matrix(pls.out[[4]], ntrain, ncomp))
Ztrain$y <- Ytrain
Ztest <- as.data.frame(scale(Xtest, center = pls.out$meanX,
scale = FALSE) %*% pls.out$R)
if (is.null(priors)) {
lda.out <- lda(formula = y ~ ., data = Ztrain)
}
else {
lda.out <- lda(formula = y ~ ., data = Ztrain, prior = priors)
}
predclass <- predict(object = lda.out, newdata = Ztest)
return(list(predclass = predclass, ncomp = ncomp,regressionPLS=pls.out))
}
```

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